Investigating an Assessment Design that Prevents Students from Using ChatGPT as the Sole Basis to Pass Assessment at the Tertiary Level

Abstract

This paper investigated how to design undergraduate assessments that could not be adequately answered by ChatGPT. The paper was embedded in the revised Bloom’s Taxonomy as a theoretical model. ChatGPT has presented significant challenges to lecturers when setting assessments at the tertiary level. There is enormous potential for students to attempt to use ChatGPT to write and pass assessments. Design Based Research formed the basis of this paper’s research design. Qualitative research methods were used to interpret recordings of interaction with ChatGPT during Hermeneutic research cycles. The paper found that it was possible to design an assessment that could not be satisfactorily answered solely by ChatGPT. Interactions with ChatGPT were found to be an essential aspect of the research process. In light of the findings, efforts should be made to revise undergraduate assessments to encourage students to engage with them rather than copy and paste from ChatGPT. The paper recommended ChatGPT as a useful tool or form of interactive Google that can support writing assessment but is unable to replace the student effectively. The paper suggests that students should receive training on the limitations of ChatGPT and how they can use it more effectively in their studies.

Keywords

• assessment design
• chatgpt
• higher education
• bloom’s taxonomy